Integrated Design and Control Under Uncertainty

摘要：项目负责人：Andreas A. linninger机构：伊利诺伊大学芝加哥分校提案编号：0626162题目：不确定条件下的集成设计与控制本研究旨在研究不确定条件下高性能过程的设计与控制的统一问题。它有两个主要目标：不确定条件下过程设计与控制目标集成的决策层次。数学规划公式和求解程序，使集成设计和控制优化易于处理。为了实现这一目标，PI提出了一个包含三个层次的决策层次：动态建模、设计优化和最优质量标准。研究计划包括两个主要的研究活动：。任务a：不确定条件下设计的数学问题分解。智力优点：严密的风险和不确定性度量：集成设计和控制方法准确地量化了实际运行下的动态系统弹性。提出了最坏情况下不确定性和干扰情景的严格检测和解决方法。组合复杂性：一种新的问题分解方法，将集成设计和控制分离为两个优化层次。具有嵌入式控制的计划随机设计优化大大减少了问题的规模和复杂性。实例研究证明了该方法与现有数学规划的收敛性。该方法应显著提高集成设计和控制问题的可追溯性。新的随机优化算法：PI还提出了专门为不连续和开放式设计优化量身定制的新颖优化程序。一种具有群体学习加速的随机遗传规划将遗传算法的鲁棒性与基于梯度的数学规划的速度相结合。更广泛的影响：当今全球网络中的制造商必须交付始终满足全球客户质量要求的产品。原材料和操作条件不可避免的变化以及严格的产品规格使得稳健的工艺操作成为未来经济可行性的必要条件。这项工作预计将以以下方式影响现代过程操作：稳健过程的系统决策：我们的方法将提供分析指南，通过集成设计和控制来解决不同类型的不确定性。设计和控制的集成：供需网络的全球化将需要新颖的设计方法，使制造商能够开发和操作过程，以无与伦比的性能水平始终满足客户的需求。精确量化不确定性和风险的高保真模型将使美国工业更接近性能限制的安全运行。控制组合复杂性：克服开放式设计问题的创新理念有望影响高性能过程的设计活动，如燃料电池、能源集成和优化供应管理，其中严格满足操作约束是至关重要的。该教育计划预计将在化学工程本科课程中引入灵活的设计和控制，专门的本科研究项目（NSF REU-Site）专门涉及代表性不足的群体，并为K-14科学和数学教师提供协同机会，为城市地区的少数民族服务（NSF RET-Site）。传播计划通过出版物和专业渠道进行学术出口。

ABSTRACTPI: Andreas A. LinningerInstitution: University of Illinois ChicagoProposal Number: 0626162Title: Integrated Design and Control Under UncertaintyThis research is aimed at the unification of design and control for high performance processes under uncertainty. It has two main objectives:. A decision-hierarchy for the integration of process design and control objectives under uncertainty. Mathematical programming formulations and solution procedures to make the integrated design and control optimization tractable.To achieve this goal, the PI proposes a decision hierarchy with three levels: dynamic modeling, design optimization and optimal quality standards. The research plan involves two main research activities:. Task-A: Mathematical Problem Decomposition for design under uncertainty. Task-B: Computational Advances for Integrated Design and ControlIntellectual Merit:Tight risk and uncertainty metrics: The integrated design and control approach accurately quantifies the dynamic system resilience under realistic operation. Rigorous detection and resolution of worst-case uncertainty and disturbance scenarios are presented.Combinatorial Complexity: A novel problem decomposition segregates the integrated design and control into two levels of optimization. The planned stochastic design optimization with embedded control reduces massively problem size and complexity. Case studies demonstrate convergence of the method with existing mathematical programming. The methodology should significantly improve the tractability of integrated design and control problems.New Stochastic Optimization Algorithms: The PI also proposes novel optimization procedures specifically tailored for discontinuous and open-ended design optimizations. A stochastic genetic program with population learning acceleration combines the robustness of genetic algorithms with the speed of gradient-based mathematical programming.Broader Impact:Manufacturers in today's global networks must deliver products that consistently meet customer quality demands worldwide. Unavoidable variability in raw materials and operating conditions and tight product specifications make robust process operation a necessity for future economic viability. This work is expected to impact modern process operation in the following ways:Systematic decisions for robust processes: Our methodology will provide analytical guidelines for addressing different types of uncertainties with integrated design and control.Integration of design and control: The globalization of supply and demand networks will require novel design methods that enable manufacturers to develop and operate processes that consistently meet customer demands at unparalleled performance levels. High fidelity models to tightly quantify uncertainty and risk will empower U.S. industry to safely operate closer to performance limits.Taming the Combinatorial Complexity: Innovative ideas to overcome the open-ended design problems are expected to impact design activities for high performance processes like fuel cells, energy integration and optimal supply management in which tight satisfaction of operational constraints are critical.The educational plan foresees the introduction of flexible design and control into the chemical engineering undergraduate curriculum, specialized undergraduate research projects (NSF REU-Site) specifically reaching out to underrepresented groups and providing synergistic opportunities for K-14 science and math teachers serving minorities in urban areas (NSF RET-Site). A dissemination plan foresees academic outlet via publications and professional channels.